Setting up Open Journal System for CVCE – Part I

This post gives an overview of the peculiarities of Open Journal System, an open source publication tool and might be of help when considered together with OJS’s documentation. OJS is developed by the Public Knowledge Project has become the chosen publishing platform for CVCE. OJS sports a variety of features which are of relevance for us: Multi-language support, xml integration and a clean and customizable look to it.

In this blog post I describe the process of setting up Transactions in Digital Humanities, the first publication by CVCE which publishes papers from last year’s DHLU conference.

I cannot really comment on the installation process itself since thankfully a colleague of mine in the IT department took on this task. There were a few hickups at first: some of the labels were not displayed correctly as shown in the screenshot below (not that this is not the final design).

OJS features a range of different user profiles, each with associated rights and access levels. Starting with “reader” and “author”, the roles include section editors, layout editors, proofreaders, editors, a journal manager and finally an admin. OJS explain their respective roles rather well. In an ideal world you would have a team of people, each with their respective task working on such a project who would seamlessly interact with each other and pass on tasks from one step to the next. In the real world, one person needs to manage a range of tasks. Thankfully, OJS lets users take on more than one role.

This can get confusing however: Once logged in you put on your author hat and submit an article using a detailed and nicely configurable submission process. This process includes the acknowledgement of copyright issues, metadata self-classification, file upload etc. Once an article is submitted, a section editor or an editor needs to assign a reviewer to the article. To do this, you need to click (in my mind: counter intuitively) on “My Journals” in the right navigation pane.

This brings you back to an overview page which bundles the different roles associated with your user id and provides handy updates on the progress of different publications.

As an editor you are free to assign reviewers, add their respective recommendations (accept/reject) and forward the task to layouters and proof-readers who are able to upload the edited versions of the files they have been working on. OJS stores these versions separately, albeit only the admin has access to the quite rudimentary file browser. OJS offers a quite handy, yet easily overlooked navigation through the publishing process:

You might find it hard to find the “Complete” commands which are associated with each task in the user interface, again in my mind counter intuitively, they are positioned in the middle of the page and are easily overlooked.

Once everything is proof-read and layouted, OJS asks you upload the final version of the file. I chose to edit an HTML file and to upload it directly in the Layout section, selecting the “Galley” option. Not that there seems to be an annoying bug which causes problems when parsing H2 (second level) captions. Replacing them with H3 (third level) captions in an editor solves this.

The test file I worked with came in ODT format. Images embedded in the text and exported to HTML will contain machine-created filenames which will not be recognized by OJS. Instead I embedded images manually in an editor, for example:

IMG SRC=”figure_1.jpg” NAME=”graphics1 WIDTH=741 HEIGHT=536>

The file will be uploaded and displayed above. Click “Edit” next to the uploaded file to change the label of the link to the uploaded file (I stick with “HTML”. Albeit a bit hidden, this editing section is quite useful for any revisions. Here you can replace the uploaded file in case you run into formatting problems and crucially: Upload pictures which accompany the text.

Note that once you close this editing section, you will jump back to the previous page but end up in the deviously similarly looking Copyediting section above the Layout section.

Continue by “Completing” the Proofreading section and the article should be published.

Helpful links:

Detailed User Guide

Frequently Asked Questions

OJS Forum

CVCE at Talk of Europe Creative Camp with CRP Lippmann & Lab1100

The Talk of Europe Creative Camp was organised by Max Kemman and Astrid van Aggelen and featured research projects and presentations by 16 researchers in Computer Science and the Humanities – a big thanks for all their hard work!

What do you do when you have all the debates in the EU parliament from 1992 onwards digitized, in RDF and you are just one SPARQL query away from them? If you have one week to work with specialists in network data visualization and management? First of all you need to bridge the gap between domain experts and ask how this data can be used to answer research questions in European studies and Computer Science. This turned out to be as hard as expected.

This week nevertheless yielded a method which helps us to detect unexpected speaker appointments by Members of the European Parliament (created by Fintan McGee of our neighbouring research institute CRP Lippmann) and an import functionality for Nodegoat which makes it easy to pull and visualise data from the Talk of Europe’s SPARQL endpoint (created by Pim van Bree and Geert Kessels of Lab1100). For CVCE this was an excellent opportunity to experiment with new ways of extracting and visualising information from structured data repositories.

For starters: A little of bit on networks

To explain our work a short intro is needed: Graphs like the one below are so-called 1-mode networks. This means that there is only one type of nodes (in this case people) connected to each other. Imagine that the people in this network are connected to each other because they all are members of the same sports club.

Mac OS X:Users:marten.duering:Desktop:1mode.png

In this example, a 1-mode network visualisations represents group affiliations by showing links between all members of a group. This works fine here but very quickly becomes cluttered when a group has a large number of members.

You can also represent this kind of information using a 2-mode network; a network which has two types of actors (people, sports club). It is important to mention that in 2-mode networks ties can only exist between actors of different types (person -> sport club), never within one type of actors (person -> person).

Mac OS X:Users:marten.duering:Desktop:2mode.png

2-mode networks are also sometimes called affiliation networks or bimodal networks and are particularly well-suited to identify overlaps between groups as illustrated in the graph above. In both examples it is clear that Laura is the person who is part of both groups. 2-mode visualisations are however often leaner than 1-mode networks since they represent an affiliation of a person by one tie alone and merely imply the links between members of a group.

Both 1-mode and 2-mode networks can be described mathematically as well. There are numerous ways to describe how central a node is in a network and how different nodes cluster together. Fintan’s work focuses on algorithms which are used for 2-mode networks and networks with more than 2 types of actors, so-called multimodal networks. 2-mode networks can be projected into 1-mode networks. This means that instead of 2 types of nodes we end up with only one. A tie between these nodes is added when – in our example – two people are members of the same club. This works just fine in the above examples. But as as Fintan highlights, projections can lead to a loss of information: One actor may be a member of three clubs and end up with the same connections as someone who only attends two clubs. Redundancy is one way to measure this loss of information.

Redundancy may reveal irregularities

Getting the opportunity to speak is a privilege in the EU parliament and very often the same people are chosen to speak on their area of expertise. But sometimes they don’t. Domain experts Frédéric Allemand (CVCE) and Bjørn Høyland (Oslo University) showed interest to detect the latter. It turned out that Redundancy, a concept developed in graph theory might do just that, as Fintan discovered during the week.

Drastically simplified, Redundancy describes how irreplaceable a node is in a 2-mode graph. In other words: Nodes which can be removed from a graph without changing its overall structure when it is projected into a single mode are considered to be highly redundant.

The graph below was created by Fintan and shows connections between Members of the European Parliament who spoke on certain agenda items in the year 2010 (527 nodes, 595 edges). An interactive version of this graph, realized with the sigmajs plugin for Gephi, is also available.

                Mac OS X:Users:marten.duering:Desktop:toe-fig1.png

Click here to launch an interactive version of this Graph

Only those MEPs are shown who have a low level of redundancy (<0.5) which means that speakers with very atypical combinations of topics on which they speak will be highlighted. An example is Mike Nattrass (United_Kingdom) who spoke on contrasting subjects such as:

  • Ban on commercial whaling (debate)

  • Implementation of the first railway package directives (debate)

  • Progress made on resettling Guantanamo detainees and on closing Guantanamo (debate)

  • Protection of animals used for scientific purposes (debate)

  • Welfare of laying hens (debate)

This is where our journey ends and domain experts need to take a close look at the data to identify the meaning of the graph and link back their observations to the context knowledge which is and remains essential for the humanist analysis of the parliamentary debates.

From SPARQL to Network via Nodegoat

For our second project, Geert Kessels and Pim van Bree of Lab1100 have developed a new feature for Nodegoat which allows users to load data directly from the Talk of Europe SPARQL endpoint (or any other). This will make it significantly easier to explore the debate data for anyone who can write a query. Nodegoat might well be the to-date easiest way to set up a relational database, fill it with data and visualise the data as a social or spatial network and to observe changes over time.

That said, it is no trivial task to write such a query. But its advantage lies in the precision with which one can download a very particular constellation of data points.

User can define custom import templates which define how the data will be organized and linked to each other in Nodegoat.

Once these two steps are sorted, the data is ready to be visualised. Nodegoat supports the visualisation of social graphs but also combinations of social graphs and maps. You can check out a few examples on their website and use this User Guide to setup your own project. Sadly we ran out of time to test this new feature and develop queries together with our domain expert.

All in all, this was a great opportunity to start a collaboration between the CVCE DH Lab, CVCE EIS and Fintan of CRP Lippmann and Geert and Pim of Lab1100.

Scrum Methodology & it’s Practical Use at CVCE

Services and tools developed by the Digital Humanities Lab for must cater to a variety of target audiences and their specific needs. More often than not, at the start of projects, these needs are not yet fully developed and are highly uncertain. So whilst we have a detailed overview of a product and a corresponding set of basic user requirements, it is not always possible to plan at the the inception of a project exactly what detailed form the end-product will take.  The user needs and knowledge become clearer and more established during the iterative process of technological development, which can stimulate creativity, discussion and facilitate the emergence of further user requirements. Therefore, for future projects starting between 2014 and 2017 we are looking to adopt a pragmatic methodology that enable us to efficiently move from an idea to a stable product.

We aim to use an empirical approach for developing projects and their associated products, through the adoption of the Scrum framework. The Scrum framework is a methodology for developing and sustaining complex products. It is suited to circumstances where solutions are required for complex adaptive problems requiring creative approaches (source? Mountain goat?). It is based on the following realisims:

  • You can’t plan your way out of uncertainty
  • The point in a project when you know the most is when it is complete

With a focus on highly user-centred development process that places user needs (and their uncertainty) at its heart, scrum affords transparency of the development cycle to our internal stakeholders (researchers in European integration studies) and will ensure best value to our external users (scientific communities, teaching and lifelong learning communities, society at large). It will allow inspection of products regularly, starting at an early development stage.  It also provides a framework to adapt products based on the users’ knowledge gained during the development process. Thus, it should help us deliver more robust, useful and usable solutions.

What is Scrum?

In essence Scrum is a methodology based on AGILE, where product requirements and solutions evolve as a consequence of collaborations between teams, product owners and their stakeholders. Scrum can be applied to many different types of projects but is commonly adopted by software development projects as it is highly suited for rapidly changing or emergent requirements, with the aim to create software delivers more value ( and can be summarised in the following high level, simple steps:

  • A Product Owner creates a prioritised, ordered list of items (akin to a wish list) known as a product backlog
    • Often the items are written as user stories
    • Items at the top of the list are written with more detail
    • The backlog is continuously evolving
  • Then in a sprint planning meeting, a subset of the items on the product backlog are selected  by the scrum team and placed into a sprint backlog.
  • The sprint backlog forms the tasks and activities of the a sprint
    • a 1 to 4 week period within which the items on the sprint backlog must be completed
  • During the 1-4 week sprint period a 15 minute daily fixed scrum meeting
    • Same time, same people, same place .
    • The aim is to understand:
      1. What work was completed yesterday?
      2. What is planned for today,
      3. Are you facing any problems?
  • The ScrumMaster helps resolve any impediments to progress during the sprint
  • Following the completion of a Sprint, there should be a potentially releasable iteration of product that can be shown to the product owner and stakeholders during a sprint review
    • If the sprint is two weeks long then it is suggested a sprint review meeting should last two hours.
  • A sprint retrospective is held to review the sprint
    • what went well?
    • What could have been improved?
    • What actions to take in the next sprint.
  • Repeat process for the next set of items ordered at the top of the backlog

    Scrum Methodology , source: click on image


How will we implement Scrum methodology at CVCE?

The first step is to identify a few projects which would really benefit from a Scrum approach and begin from here, then we will use a snowball effect to then adopt it for other projects after the benefits and business value are clearly visible to all our stakeholders. I have been on the Scrum Product Owner training course (which I enjoyed immensely) and my college has participated in the ScrumMaster training course.

At the CVCE there will be three main departments involved developing projects and products using Scrum

  1. European Integration  Studies (EIS)  – comprising of social science and humanities researchers
  2. Digital Humanities Lab (DH Lab) – comprising of digital humanist researchers who are the interface between EIS and DevOps.
  3. Development & Operations (DevOps) – comprising of computer scientists and media technologists

The project that we have selected to be our pilot for the adoption of Scrum is one where we are working on evolving and improving the interface, our data model and data enrichment process for the CVCE document object repository. As part of this evolution we are integrating a metadata zone within the interface and data model to enable EIS to easily provide metadata in line with the international standards of Dublin Core, for all the objects they create. This will be combined with a citation generation service to provide internal users (CVCE historians) of the repository and readers accessing the repository via the website with automatically generated citations for all resources, conforming to ISO 690 numeric French standards. To complement this, there is a need to develop a metadata quality control process to ensure consistency of the authority lists that are created as part of our metadata policy.  It is this project that we are implementing with Scrum.

citation user stories

Example of our organised user story descriptors for items associated with citations

A member of the DH Lab is the product owner ,EIS our stakeholders and various staff from DevOps and the DH Lab comprise the scrum team. The product backlog is emerging based on sets of user stories derived from interviews with users and observations of how they are currently working and the strategic objectives. We are working in 2 week sprints cycles and are currently half way through sprint 4.

To mange the scrum we are using JIRA, to both manage the backlog and organise and plan our sprints.

Thus far we are enjoying working in this way and our stakeholders appear happy. I will post further updates and details of our progress as they emerge.

Talk of Europe – Travelling CLARIN Campus

In October we will be participating in a one week creative camp, organised by the Talk of Europe – Travelling CLARIN Campus project (ToE-TCC). Funded by Dutch agencies NWO and OCW, the project follows up on the PoliMedia project, which linked entities in Dutch parliamentary records to corresponding media sources archived by the Netherlands Institute for Sound and Vision.

The CVCE was successful with two proposals submitted to ToE-TC, both focused on exploring social graphs.

  1. Visualising Co-occurrence networks of the plenary debates of the European Parliament
  2. Exploring the potential of multimodal graphs for modelling European Plenary Debates

We are excited to participate in travelling campus, as we are looking forward to finding new ways of structuring parliamentary data. We look forward to exploring how we can use such tools, techniques and data structures to shape future developments of the CVCE research infrastructure and develop new ways of exploring our collections.

There are three aims for the one week event, scheduled for 6-10 October 2014:

First Aim: “To translate the proceedings of the European Parliament debates (europarl) to CLARIN standards. In other words, the europarl data is curated to linked data so that it can be linked to and reused by other datasets and services. An interesting aspect of this dataset is that its available in 21 languages, enabling to link to other datasets in as many different languages. (…)

Second Aim: To research how this linked data can be exploited for use by humanities scholars. The combination of linked datasets with the base available in 21 languages should allow research questions not yet feasible. As such, interlingual comparative research through digital tools becomes possible. In comparison, where PoliMedia focused on how Dutch debates were covered in the Dutch media, the europarl data could be analysed to compare how European Parliament debates are covered in Dutch versus Polish media. Political scientists could analyse how subjects from EP debates relate to subjects in debates of national parliaments. In order to build tools helpful, we will investigate user requirements and possible research questions from humanities scholars. This second aim will be undertaken by Max Kemman, Martijn Kleppe and Henri Beunders from the History department of EUR.

Third Aim: To spark a transnational, European collaboration to create tools for scholars to analyse linked datasets. To this end, three meetings of a week will be organised in which teams from all CLARIN countries are invited to participate. Think hackathon, but a week long and with a European focus.”

The European parliamentary debates have been processed and are now available in RDF format. RDF, commonly associated with the buzz-word “Linked data“, “is based upon the idea of making statements about resources (in particular web resources) in the form of subject–predicate–object expressions. These expressions are known as triples in RDF terminology” (Wikipedia article on RDF). RDF is highly flexible and allows users to formulate very precise queries on their datasets.

A simple social network graph

The first proposal, in cooperation with Dr Fintan McGee of our neighbouring research centre CRP Lippmann, will explore the extent to which multimodal network analysis can be fruitfully applied to the study of the parliamentary debates. Where one-mode network visualisations can only represent one type of actor in a network (e.g. people), multimodal networks are capable of representing multiple types of actors, e.g. people, institutions, texts and places. This approach bears the potential to represent more closely the complexities of real-world networks.

An example of a geographic social network
(source: Nodegoat).

The second proposal was submitted with Lab1100, a Dutch company which develops Nodegoat. Nodegoat offers its users with simple yet powerful instruments to create relational databases online and visualise their data in form of maps and network graphs. Lab1100 will develop a way to link ToE-TCC data directly to Nodegoat using the formers SPARQL endpoint. This will ensure very quick and highly flexible data import and visualisations of the data.

CVCE researcher Marten Düring and Frédéric Allemand, Coordinator of the European Integration Studies Department at CVCE will participate in the project.

Digital Humanities LAB at CVCE – why we have a blog

The Digital Humanities lab at the CVCE is an interdisciplinary team, whose goal is to participate in the development of the CVCE’s innovative research infrastructure for European integration studies.

This blog will provide the DHLab with a forum for the exchange of information and ideas associated with our ongoing digital humanities projects. It will provide the opportunity to discuss the CVCE’s projects we are working on and the issues and challenges we face developing tools and techniques for multi-lingual digital  research environments using a wide variety of data types (pictures, text, video, maps cartoons etc) for developing novel enhanced publications.